September 2013
Message 64

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[Met-jobs] Research Associate Position at CICS at the University of Maryland (USA)

From "Roger Brugge" <>
To "" <>
Date Wed, 25 Sep 2013 10:16:27 +0000

Forwarded from CLIMLIST...

Vacancy: Research Associate, Cloud Dataset Development and Analysis

The Cooperative Institute for Climate and Satellites (CICS) at the
University of Maryland seeks to fill a professional scientific position
for its collaborative research as a Cooperative Institute with the
National Oceanic and Atmospheric Administration (NOAA). This position
will be associated with the Air Resources Laboratory in NOAA Research.
The position will be located at the NOAA Climate & Weather Prediction
Center in College Park, Maryland. The position is funded for one year

This ongoing project involves the development and validation of a
homogeneity-adjusted dataset of cloud cover from weather observations
for the past ~50 years, comparison of this dataset to other sources
of cloud data and other relevant climate variables, and assessment of
variability, trends, and uncertainties in cloud data, with emphasis
on data from the U.S. The goal of the project is to improve our
understanding of past changes in cloud cover on multi-decadal scales.

The individual will contribute to the goals of the project, including:
1. Data processing and analysis of ground-based cloud data, satellite
cloud data, and/or related climate variables, and/or analysis of
climate model data for comparison to the cloud data, in order to
clarify long-term variability and trends in cloud cover.
2. Extension of existing station data to create a more spatially
complete dataset.
3. Publication of results in peer-reviewed literature and presentation
at scientific conferences.

Requirements for this position include a M.S. (PhD preferred) in a
field related to climate studies, proficiency with a programming
language (FORTRAN is preferred), and with scientific graphics software,
and demonstrated ability to work independently and analyze scientific
data with minimal supervision. Knowledge of and experience with issues
relating to extracting long-term climate signals from weather
observations or satellite records will be considered a plus.
Familiarity with methods to extend sparse data to create a spatially
and temporally more complete dataset is also a plus. The candidate
must be able to work well with others and to communicate effectively
both orally and in writing.

To Apply: Interested candidates should send a CV with a list of at
least 3 professional references and a cover letter explaining how
your qualifications meet the posted requirements to

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